Application of Machine Learning to Pharmaceutical Development

The application of machine learning continues to grow rapidly in a variety of industrial settings. In pharmaceutical development in particular, Machine Learning methodologies have been adopted to accelerate process optimization and material characterization, a trend that is anticipated to rise with the increased rate of data digitization.  The goal of the program is to develop the skill set necessary to evaluate and apply the growing portfolio of algorithms from the open source ecosystem and deploy them in the appropriate context.  In addition to covering a multitude of Machine Learning algorithms (generalized linear regression, non-linear regression, regularization methods, random-forest, neural networks, Markov processes, etc.), the program will emphasize the generation of contextualized visualization tools to adequately present results to a wider non-expert audience as well as health authorities, a key aspect of the successful implementation of Machine Learning in pharmaceutical development.

 

Application of Machine Learning to Pharmaceutical Development Degree Requirements

Required courses:

MA 541	Statistical Methods	3
MA 576	Optimization models in Data science	3
CHE 542	Data Science in Pharmaceutical Development	3
CHE 543	Machine Learning in Pharmaceutical Development	3